Railway Wheel Flat Recognition and Precise Positioning Method Based on Multisensor Arrays

Abstract

Featured Application: Wheel flats are one of the most threatening defects during the service lifespan of railway vehicle wheels. This study proposes a new long-term monitoring method for wheel flats based on multisensor arrays. The dynamic strain responses of rails are captured by sensor arrays mounted on the rail web, ensuring that all the wheels are assessed during the train passage. Through data fusion among multiple sensors, the method locates the specific position of wheel defects. This study provides potential guidance for the maintenance of vehicles soon after the occurrences of defects.Abstract: Wheel flats have become a major problem affecting the long-term service of railway systems. Wheels with flats create intermittent impact loads to trains and rails. This not only accelerates the deterioration of vehicle and track components but also leads to abnormal wheel-rail contact conditions. An effective method for detecting wheel conditions is urgently needed to ensure the operation of the railway and provide guidance for the repair of wheels. However, most previous researches have used qualitative detection methods, and hence have been unable to achieve accurate positioning of the wheel flats. In addition, the theoretical basis for the layout scheme for wheel flat detection sensors is lacking, making it impossible to meet the needs of field applications. In this study, we simulated the spatial distribution characteristics of rail strain, under different wheel flat conditions, and based on this, a layout scheme of multisensor arrays was proposed which more effectively captured the responses of the wheel flats. A wheel flat recognition and precise positioning method based on multisensor fusion was designed. The algorithm was validated through the combination of experimental and simulation methods. The result shows that the algorithm can ideally detect and locate the wheel flats under complex conditions.

Special Issue on Novel Approaches for Structural Health Monitoring

“…The study published in [12] concerns the major problem of wheel defects detection and their long-term monitoring, to enhance a more sustainable maintenance planning of trains and rails while ensuring high standards of serviceability and safety. In particular, this work focuses on wheel flats, well-known defects responsible for anomalous impacts on the track that accelerate the degradation of both the track and the wheel itself.…”

Railway Vehicle Wheel Flat Detection with Multiple Records Using Spectral Kurtosis Analysis

“…Since the spectral characteristics of the amplitude modulation component (AM) and the frequency modulation component (FM) are relatively simple and closely related to the fault-related frequencies, the wheel flat information can be disclosed in the spectrum of the AM component and the instant frequency spectrum of the FM component. Therefore, to separate these low-frequency modulation components from the high-frequency carrier signal, a demodulation method can be used [32,33].…”

Wheel Flats in the Dynamic Behavior of Ballasted and Slab Railway Tracks

“…Furthermore, high levels of noise and excessive vibration are generated by this type of wheel defect. Wheel flats are mainly due to anomalous wear of the wheel due to sudden braking or due to insufficient adhesion force between the wheel and the rail [2].…”